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International Journal of Wildland Fire
Article . 2024 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Predicting terrain-induced wind turbulence for smokejumper parachute operations

Authors: Natalie Wagenbrenner; Loren Atwood; Jason Forthofer; Isaac Grenfell;

Predicting terrain-induced wind turbulence for smokejumper parachute operations

Abstract

Background Terrain-induced turbulence is dangerous for smokejumpers parachuting into complex terrain and results in numerous serious accidents annually. Aims We quantify wind modelling system WindNinja’s ability to reproduce terrain-induced effects on the mean wind speed and turbulence in complex terrain. We assess WindNinja’s suitability for use in identifying safe jump spots during smokejumper operations in complex terrain. Methods We evaluate the model’s ability to reproduce mean wind speed, mean wind direction and turbulence kinetic energy (TKE) measured by sonic anemometers and lidar scanners over a ridge–valley–ridge system collected under near-neutral atmospheric conditions during the Perdigão field campaign. We conduct a WindNinja simulation to examine the wind and turbulence conditions during the 2021 Eicks Fire smokejumper accident. Key results WindNinja can reproduce both mean wind speed and turbulence characteristics induced by the terrain. WindNinja revealed critical turbulence information that could have been useful to smokejumpers during the Eicks Fire jumping operation. Conclusions WindNinja’s ability to reproduce key features in the mean wind speed and turbulence fields induced by the terrain make it suitable for use as an aid in identifying safe jump spots in complex terrain. Implications Findings from this work will reduce parachute accidents and increase the safety of aerial firefighter operations.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
hybrid